Ziyu Chen

Ziyu Chen is a Marshall H. Stone Visiting Assistant Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. His research focuses on intersections of machine learning, mathematical statistics, and signal processing, with emphasis on equivariant models, time-frequency analysis, and generative frameworks. He has contributed to theoretical guarantees for group-invariant algorithms and applications in biomedical signal analysis.

Education background not explicitly listed, but his research trajectory suggests advanced training in applied mathematics and computational statistics. Research interests include:

• Generative Models with Symmetry Exploitation
• Statistical Guarantees for Machine Learning Algorithms
• Synchrosqueezed Transforms for Signal Analysis
• Graph Neural Networks and Spectral Embeddings

Recent publications emphasize methodologies for handling symmetric data structures, improving time-frequency localization, and clinical applications of machine learning. Notable work includes equivariant score-based models, group-invariant GANs, and disentangling frequency modes in complex time series.

Recipient of teaching awards at UMass Amherst, though specific prizes not listed. No documented grants or advising roles found in provided text. Active in interdisciplinary research spanning mathematics, computer science, and biomedical engineering.